Path Tracking Control in Autonomous Agricultural Vehicles: A Systematic Survey of Models, Methods, and Challenges
Chuanhao Sun, Jinlin Sun, Shihong Ding, Qiushi Li, Li Ma
Abstract
With the advancement of precision agriculture and agriculture 4.0, path tracking control technologies for autonomous agricultural vehicles (AAVs) have become essential for achieving efficient and automated operations. This paper begins by introducing the theoretical framework of AAV path tracking, including its applications across various working scenarios such as dry fields, paddy fields, and orchards, and establishes corresponding vehicle dynamics models suited to these environments. AAVs are classified into wheeled and tracked types based on structural characteristics and specific operational requirements. Subsequently, path tracking control methods are divided into linear and nonlinear approaches according to their system applicability, with detailed discussions on the implementation and adaptations of these strategies in real agricultural settings. Given its strong robustness and extensive adoption, sliding mode control receives particular emphasis in this review. Finally, the paper addresses persistent challenges in complex farmland environments and identifies future research directions aimed at enhancing practicality and adaptability. This review provides a comprehensive and structured analysis of AAV path tracking technologies, with a focus on environmental adaptability and operational feasibility, thereby offering valuable insights for further research and technological development in precision agriculture.